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DBMS > Apache Impala vs. GigaSpaces vs. Microsoft Azure AI Search vs. Teradata Aster

System Properties Comparison Apache Impala vs. GigaSpaces vs. Microsoft Azure AI Search vs. Teradata Aster

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGigaSpaces  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionAnalytic DBMS for HadoopHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsSearch-as-a-service for web and mobile app developmentPlatform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMSDocument store
Object oriented DBMS infoValues are user defined objects
Search engineRelational DBMS
Secondary database modelsDocument storeGraph DBMS
Search engine
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score5.59
Rank#63  Overall
#7  Search engines
Websiteimpala.apache.orgwww.gigaspaces.comazure.microsoft.com/­en-us/­services/­search
Technical documentationimpala.apache.org/­impala-docs.htmldocs.gigaspaces.com/­latest/­landing.htmllearn.microsoft.com/­en-us/­azure/­search
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGigaspaces TechnologiesMicrosoftTeradata
Initial release2013200020152005
Current release4.1.0, June 202215.5, September 2020V1
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2; Commercial licenses availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java, C++, .Net
Server operating systemsLinuxLinux
macOS
Solaris
Windows
hostedLinux
Data schemeyesschema-freeyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyesyesyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nono infoXML can be used for describing objects metadatanoyes infoin Aster File Store
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-99 for query and DML statementsnoyes
APIs and other access methodsJDBC
ODBC
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
RESTful HTTP APIADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C++
Java
Python
Scala
C#
Java
JavaScript
Python
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesnoR packages
Triggersnoyes, event driven architecturenono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
yes infoImplicit feature of the cloud serviceyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyes infoMap-Reduce pattern can be built with XAP task executorsnoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosRole-based access controlyes infousing Azure authenticationfine grained access rights according to SQL-standard

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More resources
Apache ImpalaGigaSpacesMicrosoft Azure AI SearchTeradata Aster
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